Udit TakkarandGitHub
7a9fdd5a0c
## What does this PR do? This PR adds https://vercel.com/blog/introducing-react-best-practices for your coding agent using `npx add-skill vercel-labs/agent-skills` command The skills are added to `.claude/`, `.cursor/`, and `.opencode/` directories to provide React and Next.js performance optimization guidance for AI-assisted workflows. ## Updates since last revision Addressed Cubic AI review feedback for issues with confidence >= 9/10: - **rerender-dependencies.md** - Replaced `console.log(user.id)` with `fetchUserDetails(user.id)` to avoid logging sensitive information - **server-after-nonblocking.md** - Removed `sessionCookie` from `logUserAction` call to avoid logging sensitive authentication data, added `await` to async call - **bundle-conditional.md** - Added `loadError` state and `setLoadError` setter to fix undefined `setEnabled` reference - **advanced-event-handler-refs.md** - Updated `useWindowEvent` handler signature to accept `Event` parameter and forward it to the stored handler - **rerender-derived-state.md** - Closed `<nav>` elements in both examples for valid JSX Fixes applied to both `.claude` and `.cursor` skill directories for consistency. ## Mandatory Tasks (DO NOT REMOVE) - [x] I have self-reviewed the code (A decent size PR without self-review might be rejected). - [x] N/A I have updated the developer docs in /docs if this PR makes changes that would require a [documentation change](https://cal.com/docs). If N/A, write N/A here and check the checkbox. - [x] N/A, I confirm automated tests are in place that prove my fix is effective or that my feature works. ## How should this be tested? These are documentation files for AI coding agents. No runtime testing required - review the markdown files to verify the example code snippets are correct. ## Checklist for human review - [ ] Verify example code snippets in the skill files are syntactically correct - [ ] Confirm the fixes don't introduce new issues in the documentation examples - [ ] Check that `.claude` and `.cursor` directories have consistent content --- Link to Devin run: https://app.devin.ai/sessions/f7f7e67fdeea4b22a4817d63ed9e1759 Requested by: unknown ()
42 lines
1.3 KiB
Markdown
42 lines
1.3 KiB
Markdown
---
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title: Cross-Request LRU Caching
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impact: HIGH
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impactDescription: caches across requests
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tags: server, cache, lru, cross-request
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---
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## Cross-Request LRU Caching
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`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
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**Implementation:**
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```typescript
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import { LRUCache } from 'lru-cache'
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const cache = new LRUCache<string, any>({
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max: 1000,
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ttl: 5 * 60 * 1000 // 5 minutes
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})
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export async function getUser(id: string) {
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const cached = cache.get(id)
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if (cached) return cached
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const user = await db.user.findUnique({ where: { id } })
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cache.set(id, user)
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return user
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}
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// Request 1: DB query, result cached
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// Request 2: cache hit, no DB query
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```
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Use when sequential user actions hit multiple endpoints needing the same data within seconds.
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**With Vercel's [Fluid Compute](https://vercel.com/docs/fluid-compute):** LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
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**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
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Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)
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